Difference between revisions of "Exposure of Finnish subpopulations to fine particles due domestic wood combustion"

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==Scope==
 
==Scope==
Is there any differences between exposure of PM2.5 due wood combustion of different subpopulations in Finland?
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Is there any differences between exposure of Finnish subpopulations to PM2.5 due domestic wood combustion?
  
 
==Definition==
 
==Definition==

Revision as of 06:39, 27 April 2009


Scope

Is there any differences between exposure of Finnish subpopulations to PM2.5 due domestic wood combustion?

Definition

Purpose

This is assessment page for evaluation of exposure of finnish subpopulations to fien particles due domestic wood combustion. Calculations has been done mainly with ARcMap version 9 and R version X.

Boundaries

  • Population of Finland
    • Male/female
    • Age
    • Education

Data

  • Modeled dispersed concentrations of PM2.5 due domestic wood burning (Piltti)
  • Population data (Tilastokeskus)


Scenarios

Result

Poster abstract for ISES 2009 will be written here. Please feel free to comment.

Abstract Requirements:

  • Abstracts should not exceed 300 words (2,000 characters).
  • Abstracts reporting on research or investigations must include results. Statements such as “findings will be reported” are not sufficient.
  • Abstracts must be submitted electronically at www.ises09.org by May 1, 2009.

Calculations as Analytica version can be downloaded here.

Introduction

The domestic wood combustion is one of the most important primary fine particulate matter (PPM2.5) emission source category in Finland. In our previous study we have estimated that average intake fraction (iF) for PPM2.5 emissions originated from domestic wood combustion is 3.31 per million. In this study we estimated iF for domestic wood combustion related PPM2.5 emissions and for the different population groups.

Material and Methods

The PPM2.5 emission data was based on the Finnish Regional Emission Scenario (FRES) model. The dispersion of pollutants was based on the urban dispersion modeling system (UDM-FMI). The resulting concentration data was combined with population data using ArcGIS version 9.2. The population data was based on Statistics Finland Grid Database. The dataset contained population numbers for Finland in resolution of 250 x 250 m2 for 2004 for different age groups and for different education groups for 2005, respectively. Intake fractions were estimated by combining emission strength, concentration, population and breathing rate data. A nominal breathing rate of 20 m3/day/person was adopted in this study.

Results

The iF variation between different population groups was small. The average iF for different genders were 1.7 per million and 1.6 per million for females and males, respectively. The average iF for different age groups varied from 0.3 per million (juvenile) to 0.7 per million (children). The if varied between different education groups. The iF was highest 1.1 per million for vocational school population and lowest 0.2 per million for upper secondary school population, respectively. People with higher education had highest and people with comprehensive school education lowest exposure levels.

Conclusions

The variation in iF and in exposure levels for PPM2.5 originated from domestic wood combustion is small between subpopulations in Finland. The average exposure levels varied between 0.5 and 0.6 µg/m3.